The
Quantitative Imaging Biomarker Alliance (QIBA) is a public-private
consortium founded by RSNA with the stated mission of improving the
value and practicality of quantitative imaging biomarkers by reducing
variability across devices, patients, and time.

In
this article, I make the case that QIBA directly benefits the medical
device industry, particularly imaging equipment and medical imaging
software manufacturers, and is a catalyst for new and improved device
development and innovation. The diagram below illustrates the elements
of a typical medical device development pathway (adapted from a U.S.
Food and Drug Administration/Center for Devices and Radiological Health
white paper on medical device innovation)[1], and the specific ways in which QIBA could impact and facilitate this pathway.

Specifically, QIBA can benefit medical device innovation by:

1. Helping drive the evolution of devices to become more quantitative.
QIBA working groups help establish the clinical
value proposition and identify unmet clinical needs which motivate
investment by the medical device industry in new, innovative products
that improve productivity by being more objective, repeatable, and
accurate.

2. Setting quantitative specifications and standards for developing devices.
QIBA technical committees are setting quantitative
specifications and standards for acceptable, target, and ideal
performance against stated clinical claims and contexts. These
specifications directly drive engineering requirements for the device
industry that feed into the prototype development pipeline.

3. Providing benchmarking data and helping set performance metrics.
QIBA technical committees, such as the Dynamic
Contrast-Enhanced-MR Imaging, (DCE-MRI) Committee, are making available
reference data (phantom, simulations, clinical data) which can be used
in the device verification and validation process and to assess
performance. QIBA is working directly with other consortia and
organizations and leveraging existing data repositories where they
exist.

4.
Facilitating use of quantitative devices and methods in standardized
multi-center studies and clinical care by adoption of common protocols
and procedures.
QIBA helps speed the regulatory pathway for the
device industry by facilitating the use of devices and methods in
standardized multi-center trials that help generate clinical evidence
and efficacy data required for regulatory submissions. QIBA programs
have the potential to lead to the qualification of new quantitative
imaging-based biomarkers and their translation into practice. The
multi-industry, multi-stakeholder composition of this effort allows
companies to benefit from sharing of risk and resources to address this
key aspect of device development. By helping establish objective
measures of site qualification and compliance of the devices to QIBA
recommendations, the sample size and effect size required in clinical
studies can be reduced. Beyond regulatory approval, the evidence
generated will contribute to establishing efficacy in clinical care.

5. Educating the clinical and research community by publishing profiles, protocols, and white papers.
QIBA can lead to wider adoption and increased use of
new quantitative methods by educating the clinical and research
community of these new trends. QIBA is doing this by publishing
profiles, protocols, white papers, and educational displays and
exhibits, which in turn can drive broader utilization and lead to
reimbursement decisions.

Lastly,
the QIBA model of shared standards and cooperation by multiple industry
representatives in the pre-competitive space is not against the
commercial interests of vendors. QIBA helps lay the groundwork for
establishing common minimum standards and procedures that drive
increased use of these new devices. This does not limit the ability of
individual developers to build innovative and differentiated products
that offer proprietary features, workflow, user experience, and
performance. QIBA is well-positioned to be an essential part of the
ecosystem to drive these benefits.

Sandeep
N. Gupta, PhD, is the manager of the Biomedical Image Analysis Lab at
the GE Global Research Center and a co-chair of the QIBA Dynamic
Contrast Enhanced MRI (DCE-MRI) Technical Committee. Dr. Gupta, whose
area of expertise is in developing quantitative image analysis
algorithms, has contributed to the development of the DCE-MRI profile
with emphasis on analysis and quantification methods.

The
ability to ensure that consistent results can be obtained across
different imaging sites and scanner types is one of the keys to
successful implementation of dynamic contrast enhanced MR imaging
(DCE-MRI) in a multisite clinical trial. The most straightforward way to
demonstrate that consistent and accurate results are being generated by
a particular scanner is through the use of appropriately designed
imaging phantoms—test objects with known attributes (geometry, T1 value,
etc.) that can be scanned using clinical sequences to test system
fidelity. The most important scanner attributes for a DCE-MRI study are
the signal-to-noise ratio (SNR) achievable using a T1 weighted dynamic
sequence, the accuracy of T1 measurement, and the fidelity of the
relationship between changes in T1 and changes in signal intensity.

QIBA
has developed a phantom and image acquisition protocol to test these
parameters. The goal of this project is to develop a freely
distributable software package to allow the quick and convenient
analysis of phantom test data. The graphic user interface (GUI) for this
package, showing a typical QIBA phantom image, is shown in Figure 1
below:

The analysis software includes four main tabs:
• Region Identification—Methods
to load and save image data, to automatically generate consistently
ordered regions of interest (ROIs) within the 32 test vials, and to load
and save ROI files.
• Signal Intensity Maps—Methods to generate maps correcting for signal intensity inhomogeneity resulting from the use of a phased-array receive coil.
• Dynamic Signal Evaluation—Methods
to automatically calculate band-to-band SNR and ROI-based signal
intensity means and standard deviations for dynamic data acquired using
the QIBA phantom.
• T1 Analysis—Methods
to generate T1 maps using any of three possible acquisition techniques:
multiple flip angles, multiple inversion recovery time, or multiple
repetition time.

Each
analysis tab generates a standard report which can be directly imported
into a graphing or analysis package such as Microsoft Excel. These
reports can then be used to assess the quality of data being generated
by a particular scanner and to determine whether that scanner is
suitable for use in a DCE-MRI-based clinical trial that incorporates the
specifications contained in the QIBA DCE-MRI Profile.

Edward
Ashton, PhD, Chief Scientific Officer, is responsible for the
scientific and algorithm development for the applications for
VirtualScopics. He has extensive custom software development experience
in biomedical imaging and military surveillance and reconnaissance. Dr.
Ashton is a frequent speaker at international imaging conferences and
has authored many peer-reviewed research articles.

The Quantitative Imaging Reading RoomRSNA
2011 marked the third year for this educational showcase featuring 21
educational exhibits with visual and experiential exposure to
quantitative imaging and biomarkers. These included exhibitor products
that integrate quantitative analysis into the image interpretation
process at various stages of the workflow process, from image
acquisition to structured reporting. Participants learned from exhibits
utilizing informational posters, computer-based demonstrations and
Meet-the-Expert presentations scheduled throughout the week.

The Special Interest Session, “Quantitative Imaging Biomarkers for Clinical Care and Research,” was also well attended.

In
addition, QIBA Technical Committees met for a plenary session where
RSNA Science Advisor Daniel C. Sullivan, MD, updated the attendees on
the QIBA mission, activities, and funded projects, as well as progress
on protocols and Profiles. The five QIBA Technical Committees covering
quantitative MR, CT, and PET modalities also had an opportunity to work
together in breakout sessions on committee-specific projects.

Update on RSNA’s 2010 NIBIB Contract for Quantitative Imaging In 2010, RSNA was awarded a two-year, $2.4
million contract from the National Institute of Biomedical Imaging and
Bioengineering (NIBIB) to support RSNA's quantitative imaging and
biomarkers programs, specifically, QIBA, formed in 2007 to advance
quantitative imaging and the use of imaging biomarkers in clinical
trials and practices.

Through
the diligent work of its funded investigators and volunteers, this
contract supports a coordinated effort to establish an infrastructure
for the collection and analysis of imaging biomarker data. The long-term
objective is to establish processes and Profiles leading to acceptance
by the imaging community, clinical trial industry and regulatory
agencies of quantitative imaging biomarkers as proof of biology, changes
in pathophysiology and surrogate endpoints for changes in the health
status of patients.

Much
of the work done by QIBA committees includes groundwork experiments
with phantoms and human data that will serve as the foundation for
claims to be used in QIBA Profiles. These Profiles will serve as
standardized measuring criterion for the future—to evaluate successful
medical care—clinical and non-clinical alike.

To
date, QIBA has 26 funded projects through the NIBIB contract with a
small number of projects pending approval. As there is still much work
to be done, further avenues for funding these and future projects are
being explored.

This
issue’s In My Opinion piece, “How QIBA will Benefit Medical Device
Innovation,” by Sandeep N. Gupta, PhD, illustrates how QIBA is already
making a difference by increasing the dialogue and buzz about
standardization, the benefits of quantitation and how quantitative
measurement will ultimately benefit the patient. All of the
sub-activities and projects taken on by QIBA volunteers will ultimately
benefit patients everywhere.

Each issue of QIBA Quarterly
features a link to a dynamic search in PubMed, the National Library of
Medicine's interface to its MEDLINE database. Link to articles on: “How
QIBA Will Benefit Medical Device Innovation” here.